Power supply recovery method of active distribution network considering optimal distribution of closed-loop power flow

被引:0
|
作者
Mao, Zhipeng [1 ]
Sun, Jianjun [1 ]
Huang, Zhiqiang [1 ]
Zha, Xiaoming [1 ]
Huang, Meng [1 ]
Guo, Jiaxue [1 ]
Shen, Yu [2 ]
机构
[1] School of Electrical Engineering and Automation, Wuhan University, Wuhan,430072, China
[2] State Grid Hubei Electric Power Research Institute, Wuhan,430077, China
关键词
Cones - DC distribution systems - Electric load flow - Electric load loss - Load flow optimization - Power distribution networks - Trees (mathematics);
D O I
10.16081/j.epae.202403003
中图分类号
学科分类号
摘要
Active distribution network has flexible adjustment ability as well as fast and reliable operation ability. But the existence of soft open point(SOP), distributed generator and other equipments makes the power supply recovery model complex. It is necessary to study the fast decision-making method of power supply recovery after failure. A fast decision-making method for active distribution network load recovery scheme considering optimal distribution of closed power flow is proposed. The closed operation state of all the tie switches in the distribution network after fault removal is simulated, and the optimal power flow is solved based on the second-order cone programming to exit the lines with low voltage and small operating capacity, in order to form a benign network topology with SOP in the distribution network conducive to power supply recovery. A load recovery model based on load power factor and graded load weight is established. A load power supply recovery scheme is formulated to ensure that the off-power load can get the maximum recovery level strictly according to the priority. The simulative results of IEEE 33-bus distribution system and IEEE 69-bus distribution system show that the proposed method can be both accurate and fast. © 2024 Electric Power Automation Equipment Press. All rights reserved.
引用
收藏
页码:109 / 115
相关论文
共 50 条
  • [31] Dynamic Optimal Power Flow for Active Distribution Networks
    Gill, Simon
    Kockar, Ivana
    Ault, Graham W.
    IEEE TRANSACTIONS ON POWER SYSTEMS, 2014, 29 (01) : 121 - 131
  • [32] Generic optimal power flow for active distribution networks
    Sepulveda, Simon
    Garces-Ruiz, Alejandro
    Mora-Florez, Juan
    ELECTRICAL ENGINEERING, 2024, 106 (03) : 3529 - 3542
  • [33] Robust optimal power flow considering uncertainty in wind power probability distribution
    Dai, Leisi
    Xiao, Huangqing
    Yang, Ping
    FRONTIERS IN ENERGY RESEARCH, 2024, 12
  • [34] A network designing method for closed-loop supply chain
    Yao Weixin
    Proceeding of the 2006 International Conference on Management of Logistics and Supply Chain, 2006, : 252 - 256
  • [35] Short-circuit constrained distribution network reconfiguration considering closed-loop operation
    Macedo, Leonardo H.
    Home-Ortiz, Juan M.
    Vargas, Renzo
    Mantovani, Jose R. S.
    Romero, Ruben
    Catalao, Joao P. S.
    SUSTAINABLE ENERGY GRIDS & NETWORKS, 2022, 32
  • [36] Optimal recovery model in a used batteries closed-loop supply chain considering uncertain residual capacity
    Liu, Chang-Yi
    Wang, Hui
    Tang, Juan
    Chang, Ching-Ter
    Liu, Zhi
    TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 2021, 156
  • [37] Optimal Distribution Network Reconfiguration Considering Power Quality Issues
    Nazerian, Emad
    Gharebaghi, Sina
    Safdarian, Amir
    2017 SMART GRID CONFERENCE (SGC), 2017,
  • [38] A Method for Optimal Allocation of Distribution Network Resources Considering Power-Communication Network Coupling
    Sun, Kaitao
    Liu, Jiancun
    Qin, Chao
    Chen, Xi
    ENERGIES, 2025, 18 (03)
  • [39] Optimal Power Flow With State Estimationin the Loop for Distribution Networks
    Guo, Yi
    Zhou, Xinyang
    Zhao, Changhong
    Chen, Lijun
    Summers, Tyler Holt
    IEEE SYSTEMS JOURNAL, 2023, 17 (03): : 3694 - 3705
  • [40] Designing a closed-loop blood supply chain network considering transportation flow and quality aspects
    Fallahi A.
    Mokhtari H.
    Niaki S.T.A.
    Sustainable Operations and Computers, 2021, 2 : 170 - 189